Future of AI-driven Brick-and-Mortar Begins with Responsive Retail

We don’t live in a static world. When I “look” toward the future, I see sensing, machine learning and deep learning leading us toward a time when artificial intelligence (AI) could enable more secure and actionable retail insights with tremendous results. I envision stores using technology that always knows if shelves are stocked or not, with merchandise arranged so that retailers can gain deeper insights into inventory delivery, immediate availability, and to stay ahead of the fashion trends that drive a near constant change in stock. I imagine a store where shuffled merchandise doesn’t mean lost merchandise but instead uses technology to know where items are located and uses pattern matching via machine learning and artificial intelligence to really understand the retail environment.

Connected retail technology could also enable retail staff to say, “Hey, there’s a $ 5 item covering a $ 100 item that was really supposed to be on display; l need to fix that so that I can have can have the insight into the ROI of this endcap.” It could enable them to know that a store is merchandized properly. That people interact with endcaps and individual items.

We at Intel, along with our partners, understand that retailers are looking for answers for real-time inventory management – from ordering and delivery tracking to delivering great customer experience through merchandising insights and optimizing a workforce for maximum results – a 360-degree view. I’m encouraged to see retailers moving down this path. Unfortunately, many times the quick pace of digital disruption has resulted in islands of technology that have been cobbled together, making it difficult for retailers to glean that full 360-degree view of the store that leads to actionable insights. As technology leaders, we can help enable technology solutions that seamlessly support retailers.

A woman shops for shoes.


Localizing Inventory Management Solutions

From my perspective, improving inventory management can solve several retail issues at once. It’s a quick, cost effective entry point for most retailers. Why? First, it’s not just a missed sale if the inventory is not in its place, but it affects the customer experience. Whether a retailer offers an inviting and easy-to-understand sales process is completely irrelevant if the product isn’t on the shelf. So, for me, that’s where it starts. Inventory visibility allows for immediate localization because they’re seeing the real-time demand. Imagine a sales associate wondering, for weeks, if Christmas sweaters have arrived into a Phoenix, Ariz., store only to find out they are not due to arrive until May? It makes absolutely no sense yet hiccups in the supply chain like this occur every year. If a near real-time inventory management solutions was in place, then the retailer would have direct insights into the supply chain and could make merchandise adjustments, and understand the buying habits of not just customers, but individual stores and whole communities. The retailer could then instantly replenish inventory, or not, based on real-time demand.

One solution along these lines that I’m particularly excited about is the JDA Store Optimizer, supported by the Intel Responsive Retail Sensor. Built on Intel technology, it offers retailers an intelligent technology solution to help manage and overcome retailer’s business challenges. It tracks inventory accurately, so you always know where items are located and how many are in stock while also automatically updating store associates’ tasks. Having near real-time inventory data makes it easy to run lean, save time and money and replenish products as needed with little risk of shortages, overstocking, or preventable returns. The JDA Store Optimizer then uses this precise inventory data to automatically identify, prioritize and assign tasks that sales associates need to carry out to optimize operational efficiency, while freeing the store manager to spend more time making decisions that will improve store performance and increase revenues.

A hand touches a kiosk screen.


Enhancing Data Security and Privacy

Along with inventory insight, data security and privacy are also hot topics with retailers. When retailers deal with privacy, they approach it from an opt-in, as an enabled right into the platform. From a purely application perspective, the core platform is built from the ground up with security in mind. It’s also important to make sure that data can be isolated per application, so that if a retailer has a specific set of data they’re bringing that it’s only for them and they know they can trust that verified data. This kind of store-to-cloud security is built in from the ground up. Then there’s end-to-end data encryption, which helps strengthen data security and privacy.

From my perspective, privacy is personal. Some people are completely okay with giving away their details; other people are very guarded about it. Only 43 percent of shoppers say they are comfortable giving up personal data to a retailer—even if it is to improve their shopping experience. This is a relevant and prescient issue to retailers today. Our approach is that there needs to be a way to opt-in, a loyalty program is a great way to do that. If you paired that with opt-in facial recognition through smart video systems in stores, then the solution could also tap into more anonymized demographics to inform store layouts and endcap optimization. Do families with children tend to spend time in certain areas of the store? What about groups of female or male shoppers? That kind of anonymized demographic information could provide valuable insights.

As we approach close to 50 percent of shoppers opting-in to share their data, it’s clear that a growing number of consumers see the value in a more personalized experience. I really think it’s about what level shoppers want to opt-in and loyalty programs are probably the best approach. Moral of the story is we’re not creating the big brother state of retail. People are asking for more personalized experiences and technology can help enable that for them.

A shopper is pleased that her local store uses the Intel Retail Sensor Platform for inventory tracking. As a result, she just scored the best bag ever.


Enabling Tremendous Insights

Consumers also say that they want associates who are more knowledgeable and they want to get the right information from the right person. They want

associates who are knowledgeable about products and can recommend products which would be of best value to them and of highest quality. A recent study shows that 2 in 3 shoppers who tried to find information within a store say they did not find all the information they needed; when they were unable to find the complete information, 43 percent of customers left the store frustrated; 22 percent said they were less likely to buy from that retailer, and 41 percent more likely to shop elsewhere. It is so important to have engaged, knowledgeable, and able sales associates and the JDA Store Optimizer enables sales associates to get back to the business of being available to customers rather than just running around the store in search of inventory.

I think we can learn even more over time to make store truly responsive. In a way, the store itself is learning. The platform helps the store learn and as the store learns, it keeps up in near real-time with the changes that are happening in consumer behavior, and the retail environment. Moreover, there’s no lag time. You’re not being caught unaware.

As we’ve seen, successful retailing comes down to one thing: getting the right product into shoppers’ hands. That may sound simple, but success requires inventory accuracy, efficient sales associates, and the flexibility to quickly adapt to shoppers’ needs in near real-time. Thanks to today’s emerging retail technology solutions I’m convinced that the retail industry’s future has never looked brighter!

Visit intel.com/retail to learn more about how Intel technology is shaping the future of responsive retail. To stay informed about Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit intel.com/IoTLinkedInFacebook and Twitter.

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Retailers Get Big Sales Bump by Investing in RFID Technology

Overhead and handheld radio-frequency identification (RFID) technology is transforming brick-and-mortar retail. Today, nearly 73 percent of all retailers are implementing RFID to track their inventory. The benefit is clear: As consumer shopping behaviors and expectations have shifted dramatically in the digital age, customers now expect to find whatever they want, when they want it, and RFID has helped retailers come a long way to delivering on these expectations. Those that have implemented RFID have seen an average of over 25 percent improvement in inventory accuracy and a profit margin boosted by 60.7 percent. RFID tech spending shows no signs of slowing down, either—it’s growing at over 22 percent per year.

RFID Technology and Handhelds Versus Fixed/Overhead Solutions
But within the RFID space, a debate emerges: Which is better, handheld or overhead (also known as fixed)? There is a common misconception that handhelds provide 80 percent of the RFID benefits at only 20 percent of the cost, implying that RFID handhelds are cheaper and easier to implement than overhead RFID. If retailers are considering only the cost of hardware when making a decision, they might think they’re getting a better deal with a handheld RFID, since only a few scanners are required per store. Fixed sensors might be more expensive and difficult to deploy initially, but over time, it’s handhelds that are likely to prove more expensive. While the upfront cost for an overhead might be, on average, 30 percent higher, ongoing labor cost can be 90 percent lower with an overhead solution.

Two women shop in a store.


Transforming the Brick-and-Mortar Store with Overhead RFID Solutions
While it’s certainly true that any RFID deployment will have its benefits, a retailer will unlock the full spectrum of usage models only with an overhead infrastructure, since it’s only with an overhead solution that retailers can truly automate processes, drive labor efficiencies, get enhanced in-store digital experiences for their customers, and get real-time data with actionable insights.

Tasks performed with a handheld will take substantially more time to do than with an overhead system, and consistency and freshness of the inventory information will be affected as well. In addition, only overhead solutions can provide added benefits such as real-time inventory tracking that enables unified commerce fulfillment or in-store pickup—not to mention the many other in-store value-adds for overheads, such as interactive experience applications like smart fitting rooms, digital interactions with products, dynamic planograms, merchandise flow tracking, self-checkout, and many more.

An overhead solution is also a future-proof investment that can be leveraged as new use cases become important, such as pick-path optimization for ship from store, item location, zone management for larger stores, and consideration tracking, to name some. There is also the added ability to audit employee tasks, ensuring items are not only moved to the floor, but in the right spot. Overheads also provide better information around loss prevention and item theft and have a better ability to track display effectiveness.

Three people shop in a store.


Getting to the Sale Faster
The cost of a handheld reader goes far beyond just the price tag of the hardware. The true cost can lead to inventory distortion, a fragmented, lackluster customer experience, and higher workforce and labor inefficiencies. Because the customer experience is driven by positive personal interaction—something made possible only through an efficient workforce and accurate inventory—it’s the quality of the customer experience that will ultimately bring the process full circle with the sales transaction.

Getting to the sale faster means automating many of the in-store processes that take the retail employee’s attention away from the customer. And the way to enhance the customer experience and get to the sale faster isn’t simply to add more associates to the fold or to make current associates do more handheld RFID scanning. That will only increase operating costs and reduce customer-facing experiences. Even once a retailer has spent the time and money to train an employee on how to properly scan a store with a handheld, the inventory accuracy is still only as good as the last scan.

Intel RRS
The Intel Responsive Retail Sensor (Intel RRS) is a smart retail solution that provides retailers with the best of both the physical and online worlds. It connects the store, bringing digital convenience and intelligence, while also driving revenue growth and reinventing the customer experience. It automates previous repetitive tasks by employees, instead allowing them to focus on customer service, and it optimizes inventory management by reducing out-of-stock and misplaced items. But it also creates new sources of data that can be used to understand shopper browsing and buying habits.

Visit intel.com/retail to learn more about how Intel technology is shaping the future of responsive retail. To stay informed about Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit intel.com/IoTLinkedInFacebook and Twitter.

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Smart Agriculture: AI and the Right Compute Transforming Farming

As the director of public sector and agriculture for the Intel Internet of Things Group, I focus on technologies, ecosystems and partnerships that need technologies that solve problems in a range of areas. We believe the technologies that we focus on: retail, manufacturing, transportation and logistics, and environmental monitoring, align well with the food and agriculture value chain. The investments and uptake in technology adoption in agriculture is somewhere that we can contribute and add value and one of the most promising industries where IoT can bring transformational changes.

At the recent Forbes Live Ag Tech Summit in Salinas, Calif., a gathering of some of the smartest minds from both Silicon Valley and the global agriculture industry resulted in a key takeaway – that most people don’t realize the numerous locations where processing of agriculture and food supply exists. Like farm equipment, where sensors measure everything from water management to nitrogen levels in soil. I not only found this encouraging, but believe that we at Intel are on the right track to supporting the technology evolution in the agricultural industry.

Moo. A dairy cow.

To that end, this past year we’ve been investigating who we can work with, who we can collaborate with and how we can add value in the context of the vision of the Internet of Things (IoT) and agricultural. The potential for transformational change is tremendous.  We believe that IoT can drive greater insight to the physical world, like farming, enabling better decision-making with that greater insight to an interconnected strong and secure ecosystem. We can’t do any of this without partnerships. It’s in our DNA, to build ecosystems and partnerships that drive innovation and really increase the amount of choice in the marketplace.

We recently invested in a company called Filament who has applied blockchain to the agriculture space. Together with Intel, Filament successfully tested tracking fish, a process that begins with attaching IoT-enabled sensors to freshly caught fish, which then continues to track the fish across the supply chain, from monitoring real-time temperature and location all the way to consumers’ plate. We’re still in the early stages, but we believe that blockchain is a viable option and we hope to continue to evaluate it and contribute to this space.

Dell and Intel work to solve honeybee colony collapse.

From individual devices and new analytics opportunities like AI, machine learning, to the cloud, IoT enables sensing and the fusing of information from multiple sources, enabling informed actions for better results. Agriculture uses this entire spectrum, from sensing, analyzing the data and making decisions from the data.

To learn more about smart agriculture, read the Intel IQ article “Farming” or the case study “Keenan and the IoT create a new kind of data farm.” Watch Tony Franklin speaking about smart agriculture on Forbes Live. To stay informed about Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit intel.com/IoTLinkedInFacebook and Twitter.

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Remote Patient Monitoring: A New Standard of Care for 21st Century Healthcare Delivery

I just came from the quadrennial meeting of the 21st IAGG World Congress of Gerontology and Geriatrics, where I noticed some things worth sharing. There’s been a tectonic shift in industry framing of aging — from costs of infirmity to value of capability and contribution of elders. Not too long ago there was resistance to these notions. Today,  the World Health Organization Strategy on Ageing has codified and recast these and other concepts in a new action plan focused on functional ability that’s  being received with universal acclaim (HuffPost).

What strikes me most is that to achieve this collective vision of healthy & active living at all ages we must also see a tipping point in deployed infrastructure for care beyond the hospital setting. Providers and policymakers must accelerate and expand support for caring for people remotely and in their home. Unless remote care becomes ‘standard of care*’  with medical care, we will never get costs under control and society will forever lack a sufficient remote care digital infrastructure to support independent living into old age.

*Standard of Care: The quality of care that a health care provider should have provided, measured by the level of care that a reasonably skilled health care professional would have provided in similar circumstances. (According to MedicalMalpractice.com)

Enhancing Access

Remote patient monitoring could become a new standard of healthcare.

Don’t get me wrong. Remote and in-home care, especially remote patient monitoring (RPM) is happening, and faster than before.  In recent years, there has been an abundance of evidence demonstrating that RPM, integrated into a care plan, leads to benefits for patients, their families, communities and national health care systems overall. Through RPM, physicians, nurses, elder caregivers and other healthcare providers can gain deeper and more objective insights into patient health, and in many cases, help lead to earlier detection and diagnosis, and therefore earlier and more effective treatment and management of multiple conditions. As one ages, there are also benefits for RPM’s role in helping to maintain “functional ability,” itself essential for a healthier, more active and lower-cost aging process.

In an example of RPM delivering tremendous results, research from the University of Mississippi, Ascension Health and Care Innovations shows that RPM technologies can greatly reduce emergency room visits and hospital readmissions. Such tested RPM applications include videoconferencing with healthcare providers, tablet-based patient education and devices that can prompt and track diet, exercise and medication adherence.

RPM in particular is saving medical costs for systems that use it and improving outcomes for their patients. According to the Veterans Health Administration, RPM can reduce hospitalizations by as much as 40 percent for some diseases, leading to annual savings of $ 6,500 per patient. The estimated annual cost-savings potential of RPM, if adopted widely, could be as high as $ 6 billion.


Transforming Healthcare Policy

Access to that level of care is elusive for most unless you happen to be within one of the few systems that have deployed it. Furthermore, most deployed systems are addressing just one or a few specific conditions. There are of course exceptions in some countries outside the United States (e.g. Singapore ), but largely, comprehensive RPM care is limited and inconsistently available.  Well-defined standards of care could help RPM reach its full potential.

I believe achieving RPM as standard of care is achievable and not in some distant idealized future. The rate of deployments is increasing, the evidence on efficacy and cost savings is overwhelming and irrefutable,  patient and clinician satisfaction when they have deployed is high, and payment systems are changing to recognize and reward  remote care use.

Consider that the average Medicare spending per person doubles between the ages of 70 and 96. Chronic conditions like COPD, heart disease, diabetes, and dementia, which often develop with age, account for nearly 90 percent of U.S. healthcare costs. By connecting patients with physicians and other care providers virtually and enabling quicker ability to address emerging health concerns, RPM can save enormous health costs with respect to reduction of physician and ER visits, early diagnosis of diseases, and mitigation of hospital admissions and readmissions. Over time, investments in the widespread adoption of RPM could help control costs and improve overall care – for governments, healthcare providers and families.

We believe that, to fairly and cost-effectively treat an ever-growing number of people needing care, RPM can and must become a “standard of care” targeting not only post-acute care management for heart attack, stroke and orthopedic and neurological surgeries, but also treatment for chronic conditions like diabetes, COPD, heart disease, and dementia. Our hope is that by 2020, RPM is a medical standard of care and by 2025 at least 50 million people are benefiting annually in the United States from its deployment in medical and independent living use cases.  The technology industry is addressing the technical challenges and the remote care services vendor ecosystem has perfected the care workflows solutions.  Now, all key industry stakeholders must work together to proliferate and democratize access to remote care.  Platforms for RPM, initially deployed for medical uses, can be the digital bedrock of all distributed systems for medical and functional ability support on a national scale.

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Building the Best Autonomous Brain

When I’m bumper-to-bumper in a sea of exhaust fumes and distracted drivers, it seems like autonomous driving can’t get here fast enough. Nor can the potential rewards that come along with fully autonomous vehicles, like far fewer accidents and mobility for people who struggle to get around on their own. To do my part, I’m focusing on how building the best autonomous brain for a car will get us there faster.

5 Things to Know About Autonomous Vehicles

Every day, we’re getting closer to the technology needed to power self-driving cars. But in-vehicle compute needs are complex, and autonomous driving algorithms are changing rapidly. So, the question is: What is the best long-term path to fast, safe decision-making? It all begins with the right compute for the right task. Here are five things you should know about the complex compute for autonomous driving.


It Takes More Than Deep Learning

Artificial intelligence is just one part of the story. And beyond that, AI is more than just deep learning. Yes, deep learning is key in teaching a car how to drive, especially when it comes to computer vision. But there will be several other types of AI at work in the fully autonomous vehicle, from traditional machine learning to memory- and logic-based AI. The fully autonomous vehicle will need a wide range of computing to support three intertwined stages of self-driving: sense, fuse and decide. Each stage requires different types of compute. In the first stage, the vehicle collects data from dozens of sensors to visualize its surroundings. During the second stage, data is correlated and fused to create a model of the environment. Finally, the vehicle must decide how to proceed. System designers need a flexible architecture to support all three stages, with an optimized combination of power efficiency and performance.

With a flexible, scalable architecture of CPUs, Intel Arria 10 FPGAs and other accelerators, our Intel GO automotive solutions portfolio leads the industry with a diverse range of computing elements that support all three stages of driving. But autonomous driving is much more than just in-vehicle compute; that’s why we offer a full car-to-cloud solution including 5G connectivity, data center technologies and software development tools to accelerate autonomous driving.
Smart AI consists of sensing, fusing and deciding.


No Fixed Architecture Can Keep Pace

Before system designers can achieve level four and five driving automation, they must determine how to best use different compute elements within the system to support each type of workload.

No fixed architecture can keep pace with the speed of innovation in AI and system design. Automakers and suppliers will need to be ready to change system designs down the road. Whether it’s to incorporate new algorithms or completely rethink compute to accommodate new workloads, system designers will need a flexible, scalable architecture. Simply put, they need interoperable and even programmable compute elements that don’t require them to start from the ground up every time they want to incorporate a new feature. With a flexible architecture of CPUs, FPGAs and other accelerators, future-ready solutions offer a diverse range of computing elements that can accommodate designs that may change long after hardware and vehicle design decisions have been made.


Driving the Future

Now is a time of tremendous opportunity as we continue to research and respond to the transformational changes before us. From powering Stanford University’s robotic car to serving as a premier board member of the University of Michigan Mobility Transformation Center’s Mcity, Intel is working alongside world-renowned research teams to understand the way people interact with connected cars. Intel has built autonomous vehicle labs in Arizona, California, Germany and Oregon. Here, we’re working hand in hand with our ecosystem partners to optimize customized solutions, road-test autonomous vehicles, and work toward common platforms that will speed broad industry innovation for the promising road ahead.

Learn more about the road to autonomous driving at intel.com/automotive. To stay informed about Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit intel.com/IoTLinkedInFacebook and Twitter.

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